What Do You Get when You Mix AI, PR, and HR?

What do you get when you mix #AI, #HR, and #PR? Remixed #incentives probably…not necessarily in a good way. pic.twitter.com/FpJvZuhHtS
— ivanjureta (@ivanjureta) February 1, 2018
In April 2023, the Cyberspace Administration of China released a draft Regulation for Generative Artificial Intelligence Services. The note below continues the previous one related to the same regulation, here. One of the requirements on Generative AI is that the authenticity, accuracy, objectivity, and diversity of the data can be guaranteed. My intent below is…
Section 4 provides requirements that influence how to do the impact assessment of an automated decision system on consumers/users. This text follows my notes on Sections 1 and 2, and Section 3 of the Algorithmic Accountability Act (2022 and 2023). When (if?) the Act becomes law, it will apply across all kinds of software products,…
If any text can be training data for a Large Language Model, then any text is a training dataset that can be valued through a market for training data. Which datasets have high value? Wikipedia, StackOverflow, Reddit, Quora are examples that have value for different reasons, that is, because they can be used to train…
Opacity, complexity, bias, and unpredictability are key negative nonfunctional requirements to address when designing AI systems. Negative means that if you have a design that reduces opacity, for example, relative to another design, the former is preferred, all else being equal. The first thing is to understand what each term refers to in general, that…
In a previous note, here, I wrote that one of the requirements for Generative AI products/services in China is that if it uses data that contains personal information, the consent of the holder of the personal information needs to be obtained. It seems self-evident that this needs to be a requirement. It is also not…
I wrote in another note (here) that AI cannot decide autonomously because it does not have self-made preferences. I argued that its preferences are always a reflection of those that its designers wanted it to exhibit, or that reflect patterns in training data. The irony with this argument is that if an AI is making…